The Monitoring, Evaluation, Research and Learning (MERL) Data Manager will support the design, implementation and continuous improvement of monitoring, evaluation, research, learning and data management for the Food & Agriculture (F&A) Pillar. The role will ensure that pillar data are efficiently collected, managed, analysed, visualized and reported to generate timely, high-quality evidence for programmes implementation, adaptive management, donor accountability and organizational learning.
Monitoring, Evaluation, Research and Learning Data Manager at Equity Bank in Nairobi, Kenya
Posted
4 days ago
Apply by
2 Sept
Full Time
On Site
Senior
Banking, Insurance & Financial Services
Data, Analytics & AI
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Key Responsibilities
- Support the design, implementation and continuous improvement of Monitoring, Evaluation, Research and Learning (MERL) systems for the Food & Agriculture (F&A) Pillar.
- Develop digital data collection and administer programme databases including on DMIS platform to support efficient programme monitoring, reporting, and performance tracking.
- Coordinate the collection, validation, cleaning, integration, storage, analysis, visualization, and reporting of programme data, ensuring accuracy, completeness, and timeliness.
- Develop and maintain interactive dashboards, automated reports, and business intelligence solutions that provide real-time programme performance insights and support evidence-based decision-making.
- Provide technical support for baseline, midline, endline, outcome, and impact assessments, including data management, statistical analysis and dissemination of findings.
- Document and disseminate data best practices, innovations, and knowledge products to strengthen organizational learning and adaptive programme management.
- Build the capacity of programme teams and implementing partners in MERL methodologies, digital data systems, data analytics, reporting, and the use of business intelligence tools.
- Collaborate with internal and external stakeholders to strengthen digital MERL systems and support programme design, implementation, reporting, evaluation and continuous improvement for the F&A Pillar.
- Support development and maintaining of GIS-enabled datasets, maps and spatial analyses to support programme planning, beneficiary mapping, environmental monitoring and impact assessment.
- Stay abreast of emerging MERL methodologies, Artificial Intelligence (AI), digital technologies and data analytics best practices and recommend innovations that enhance data management, reporting efficiency, evidence generation and programme performance.
Required Qualifications
- Bachelor's degree in Data Science, Statistics, Computer Science, Monitoring and Evaluation, Agricultural Economics, Environmental Science, Social Sciences or a related field.
- A Masters' Degree will be an added advantage.
- Professional certification in Monitoring & Evaluation, Results-Based Management (RBM), Data Analytics, GIS for spatial analysis, Business Intelligence e.g Power BI/Tableau, Database Management, or Project Management (PMP/PRINCE2) will be an added advantage.
- Minimum of 10 years' experience in monitoring, evaluation, research, learning, data management, business intelligence or programme analytics within the development, agriculture, climate, environmental or related sectors.
- Proven experience developing and managing Management Information Systems (MIS), programme databases, dashboards and automated reporting solutions.
- Strong experience in data cleaning, validation, transformation, migration, integration, and quality assurance.
- Demonstrated experience administering digital data collection platforms such as ODK, KoboToolbox, SurveyCTO, CommCare or similar technologies.
- Experience using Power BI, Tableau, Excel Power Query, SQL, ArcGIS or similar analytical and visualization tools.
- Experience supporting donor-funded programmes through programme monitoring, data management, and results reporting.
- Experience conducting quantitative and qualitative data analysis and translating findings into actionable programme insights.
- Knowledge of statistical software such as SPSS, R, Python, or Stata will be an added advantage.
- Experience in agriculture, climate resilience, natural resource management, environmental conservation, renewable energy, or rural development programmes will be an added advantage.
- Strong analytical and data interpretation skills.
- Proficiency in MERL tools, methodologies and technologies.
- Results-oriented with strong attention to detail.
- High integrity, accountability and commitment to learning.
Job Details
Job Function
Data, Analytics & AI
Minimum Experience
10 years
Education Level
Bachelor’s Degree
Area of Study
Science
Field of Study
Data Science
Additional Information
How to Apply: Interested and qualified candidates should apply online through the Equity Bank Kenya careers portal. Visit the application link provided on this page to submit your application.
Show Data Systems Mastery Before You Walk Into the Interview
This role sits at the intersection of agriculture, data, and donor accountability. Hiring managers will probe how you've turned messy field data into decisions that shaped programmes — not just your tool list.
1. Map your MERL toolkit to their stack: The posting names ODK, KoboToolbox, Power BI, SQL, and ArcGIS. On your CV, list each tool you've used and add a one-line win per tool — e.g., 'Cut reporting time 40% with a Power BI dashboard.' If you lack one, say how you'd ramp up fast.
2. Quantify your data quality wins: They want proof you can clean and validate data. Prepare a story where you caught a data error that would have misled a donor report. Numbers matter: 'Reduced data entry errors by 30% through validation rules.'
3. Prepare a dashboard walkthrough: Bring a sample dashboard (even a mock) that shows real-time KPIs for an agriculture programme. Be ready to explain the logic behind each visual and how a manager would use it to act.
4. Show donor-reporting fluency: Donor-funded programmes have strict reporting cycles. Recall a time you aligned data collection with donor indicators and met a tight deadline. Mention the donor type (e.g., USAID, EU) without inventing specifics.
5. Demonstrate GIS thinking: They want spatial analysis for beneficiary mapping. If you've used ArcGIS or QGIS, describe a map that influenced programme placement. If not, take a short online course and mention your new skill.
6. Speak the language of adaptive management: MERL isn't just reporting — it's learning. Give an example where data changed a programme's approach mid-implementation. That shows you understand the 'learning' part of MERL.
7. Prepare for technical questions: Expect SQL queries, data cleaning scenarios, and questions on statistical methods. Review basic joins, pivot tables, and how to handle missing data. Practice explaining a regression or a t-test in plain language.
8. Show you can build capacity: This role trains teams and partners. Prepare a mini-training outline on using KoboToolbox or Power BI. Mention how you've mentored colleagues before — that's a plus for this role.
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Tags
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data management
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GIS
agriculture
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